Samuel Workman

I am a political scientist working at the intersection of public policy, data science, and statistics. I specialize in public policy, the bureaucracy, regulatory politics, and statistics. My interests involve text-as-data, machine learning, and statistical modeling, especially classificationj stochastic processes, and maximum likelihood methods. I teach courses in public policy, agenda setting, regulatory policy, and statistics. My current academic projects examine congressional bureaucracies, the regulatory politics of education policy, and agenda setting in food policy.

I also provide statistical consulting in the private sector, specializing in the grocery floral category. My work focuses on data-driven decision-making and management, custom reporting, and data-informed programming.